Search results for: modern method
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 20809

Search results for: modern method

18949 Language Transfer in Graduate Candidates’ Essays

Authors: Erika Martínez Lugo

Abstract:

Candidates to some graduate studies are asked to write essays in English to prove their competence to write essays and to do it in English. In the present study, language transfer (LT) in 15 written essays is identified, documented, analyzed, and classified. The essays were written in 2019, and the graduate program is a Masters in Modern Languages in a North-Western Mexican city border with USA. This study is of interest since it is important to determine whether or not some errors have been fossilized and have become mistakes, or if it is part of the candidates’ interlanguage. The results show that most language transfer is negative and syntactic, where the influence of candidates L1 (Spanish) is evident in their use of L2 (English).

Keywords: language transfer, cross-linguistic influence, interlanguage, error vs mistake

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18948 Drivers and Barriers of Asphalt Rubber in Sweden

Authors: Raheb Mirzanamadi, João Patrício

Abstract:

Asphalt rubber (AR) was initially developed in Sweden in the 1960s by replacing crumb rubber (CR) as aggregates in asphalt pavement. The AR produced by this method had better mechanical properties than conventional asphalt pavement but was very expensive. Since then, different technologies and methods have been developed to use CR in asphalt pavements, including blending CR with bitumen at a high temperature in the mixture, called the wet method, and blending CR with bitumen in the refinery, called the terminal blending method. In 2006, the wet method was imported from the USA to Sweden to evaluate the potential of using AR on Swedish roads. 154 km AR roads were constructed by the wet method in Sweden. The evaluation showed that the AR had, in most cases, better mechanical performance than conventional asphalt pavements. However, the terrible smoke and smell led the Swedish Transport Administration (STA) to stop using AR in Sweden. Today, there are few focuses on AR, despite its good mechanical properties and environmental aspects. Hence, there is a need to study the drives and barriers of using AR mixture in Sweden. The aims of this paper are: (i) to study drivers and barriers of using AR pavements in Sweden and (ii) to discover knowledge gaps for further research in this area. The study was done using a literature review and completed by interviews with experts, including three researchers from Swedish National Road and Transport Research Institute (VTI) and two experts from STA. The results showed that AR can be an alternative not only for conventional asphalt pavement but also for polymer modified asphalt (PMA) due to the same mechanical properties but the lower cost for production. New technologies such as terminal blending and using warm mix asphalt (WMA) methods can lead to reducing the energy and temperature during production processes. From this study, it is found that there is not enough experience and knowledge about AR in Sweden, and more research is needed, including the lifespan of AR, mechanical properties of AR using new technologies, and the impact of AR on spreading and leaching substances into nature. More studies can lead to standardization of using AR in Sweden, a potential solution for the use of end-of-life tyres, with better mechanical properties and lower costs, in comparison with conventional asphalt pavements and PMA.

Keywords: asphalt rubber, crumb rubber, terminal blending method, wet method

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18947 Multi-Criteria Decision Approach to Performance Measurement Techniques Data Envelopment Analysis: Case Study of Kerman City’s Parks

Authors: Ali A. Abdollahi

Abstract:

During the last several decades, scientists have consistently applied Multiple Criteria Decision-Making methods in making decisions about multi-faceted, complicated subjects. While making such decisions and in order to achieve more accurate evaluations, they have regularly used a variety of criteria instead of applying just one Optimum Evaluation Criterion. The method presented here utilizes both ‘quantity’ and ‘quality’ to assess the function of the Multiple-Criteria method. Applying Data envelopment analysis (DEA), weighted aggregated sum product assessment (WASPAS), Weighted Sum Approach (WSA), Analytic Network Process (ANP), and Charnes, Cooper, Rhodes (CCR) methods, we have analyzed thirteen parks in Kerman city. It further indicates that the functions of WASPAS and WSA are compatible with each other, but also that their deviation from DEA is extensive. Finally, the results for the CCR technique do not match the results of the DEA technique. Our study indicates that the ANP method, with the average rate of 1/51, ranks closest to the DEA method, which has an average rate of 1/49.

Keywords: multiple criteria decision making, Data envelopment analysis (DEA), Charnes Cooper Rhodes (CCR), Weighted Sum Approach (WSA)

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18946 As a Little-Known Side a Passionate Statistician: Florence Nightingale

Authors: Gülcan Taşkıran, Ayla Bayık Temel

Abstract:

Background: Florence Nightingale, the modern founder of the nursing, is most famous for her role as a nurse. But not so much known about her contributions as a mathematician and statistician. Aim: In this conceptual article it is aimed to examine Florence Nightingale's statistics education, how she used her passion for statistics and applied statistical data in nursing care and her scientific contributions to statistical science. Design: Literature review method was used in the study. The databases of Istanbul University Library Search Engine, Turkish Medical Directory, Thesis Scanning Center of Higher Education Council, PubMed, Google Scholar, EBSCO Host, Web of Science were scanned to reach the studies. The keywords 'statistics' and 'Florence Nightingale' have been used in Turkish and English while being screened. As a result of the screening, totally 41 studies were examined from the national and international literature. Results: Florence Nightingale has interested in mathematics and statistics at her early ages and has received various training in these subjects. Lessons learned by Nightingale in a cultured family environment, her talent in mathematics and numbers, and her religious beliefs played a crucial role in the direction of the statistics. She was influenced by Quetelet's ideas in the formation of the statistical philosophy and received support from William Farr in her statistical studies. During the Crimean War, she applied statistical knowledge to nursing care, developed many statistical methods and graphics, so that she made revolutionary reforms in the health field. Conclusions: Nightingale's interest in statistics, her broad vision, the statistical ideas fused with religious beliefs, the innovative graphics she has developed and the extraordinary statistical projects that she carried out has been influential on the basis of her professional achievements. Florence Nightingale has also become a model for women in statistics. Today, using and teaching of statistics and research in nursing care practices and education programs continues with the light she gave.

Keywords: Crimean war, Florence Nightingale, nursing, statistics

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18945 Traffic Density Measurement by Automatic Detection of the Vehicles Using Gradient Vectors from Aerial Images

Authors: Saman Ghaffarian, Ilgin Gökaşar

Abstract:

This paper presents a new automatic vehicle detection method from very high resolution aerial images to measure traffic density. The proposed method starts by extracting road regions from image using road vector data. Then, the road image is divided into equal sections considering resolution of the images. Gradient vectors of the road image are computed from edge map of the corresponding image. Gradient vectors on the each boundary of the sections are divided where the gradient vectors significantly change their directions. Finally, number of vehicles in each section is carried out by calculating the standard deviation of the gradient vectors in each group and accepting the group as vehicle that has standard deviation above predefined threshold value. The proposed method was tested in four very high resolution aerial images acquired from Istanbul, Turkey which illustrate roads and vehicles with diverse characteristics. The results show the reliability of the proposed method in detecting vehicles by producing 86% overall F1 accuracy value.

Keywords: aerial images, intelligent transportation systems, traffic density measurement, vehicle detection

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18944 Comparative Study of Computer Assisted Instruction and Conventional Method in Attaining and Retaining Mathematical Concepts

Authors: Nirupma Bhatti

Abstract:

This empirical study was aimed to compare the effectiveness of Computer Assisted Instruction (CAI) and Conventional Method (CM) in attaining and retaining mathematical concepts. Instructional and measuring tools were developed for five units of Matrix Algebra, two of Calculus and five of Numerical Analysis. Reliability and validity of these tools were also examined in pilot study. Ninety undergraduates participated in this study. Pre-test – post-test equivalent – groups research design was used. SPSS v.16 was used for data analysis. Findings supported CAI as better mode of instruction for attainment and retention of basic mathematical concepts. Administrators should motivate faculty members to develop Computer Assisted Instructional Material (CAIM) in mathematics for higher education.

Keywords: attainment, CAI, CAIM, conventional method, retention

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18943 Overhead Lines Induced Transient Overvoltage Analysis Using Finite Difference Time Domain Method

Authors: Abdi Ammar, Ouazir Youcef, Laissaoui Abdelmalek

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In this work, an approach based on transmission lines theory is presented. It is exploited for the calculation of overvoltage created by direct impacts of lightning waves on a guard cable of an overhead high-voltage line. First, we show the theoretical developments leading to the propagation equation, its discretization by finite difference time domain method (FDTD), and the resulting linear algebraic equations, followed by the calculation of the linear parameters of the line. The second step consists of solving the transmission lines system of equations by the FDTD method. This enabled us to determine the spatio-temporal evolution of the induced overvoltage.

Keywords: lightning surge, transient overvoltage, eddy current, FDTD, electromagnetic compatibility, ground wire

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18942 Real-Time Pedestrian Detection Method Based on Improved YOLOv3

Authors: Jingting Luo, Yong Wang, Ying Wang

Abstract:

Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

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18941 Influence of Iron Content in Carbon Nanotubes on the Intensity of Hyperthermia in the Cancer Treatment

Authors: S. Wiak, L. Szymanski, Z. Kolacinski, G. Raniszewski, L. Pietrzak, Z. Staniszewska

Abstract:

The term ‘cancer’ is given to a collection of related diseases that may affect any part of the human body. It is a pathological behaviour of cells with the potential to undergo abnormal breakdown in the processes that control cell proliferation, differentiation, and death of particular cells. Although cancer is commonly considered as modern disease, there are beliefs that drastically growing number of new cases can be linked to the extensively prolonged life expectancy and enhanced techniques for cancer diagnosis. Magnetic hyperthermia therapy is a novel approach to cancer treatment, which may greatly contribute to higher efficiency of the therapy. Employing carbon nanotubes as nanocarriers for magnetic particles, it is possible to decrease toxicity and invasiveness of the treatment by surface functionalisation. Despite appearing in recent years, magnetic particle hyperthermia has already become of the highest interest in the scientific and medical environment. The reason why hyperthermia therapy brings so much hope for future treatment of cancer lays in the effect that it produces in malignant cells. Subjecting them to thermal shock results in activation of numerous degradation processes inside and outside the cell. The heating process initiates mechanisms of DNA destruction, protein denaturation and induction of cell apoptosis, which may lead to tumour shrinkage, and in some cases, it may even cause complete disappearance of cancer. The factors which have the major impact on the final efficiency of the treatment include temperatures generated inside the tissues, time of exposure to the heating process, and the character of an individual cancer cell type. The vast majority of cancer cells is characterised by lower pH, persistent hypoxia and lack of nutrients, which can be associated to abnormal microvasculature. Since in healthy tissues we cannot observe presence of these conditions, they should not be seriously affected by elevation of the temperature. The aim of this work is to investigate the influence of iron content in iron filled Carbon Nanotubes on the desired nanoparticles for cancer therapy. In the article, the development and demonstration of the method and the model device for hyperthermic selective destruction of cancer cells are presented. This method was based on the synthesis and functionalization of carbon nanotubes serving as ferromagnetic material nanocontainers. The methodology of the production carbon- ferromagnetic nanocontainers (FNCs) includes the synthesis of carbon nanotubes, chemical, and physical characterization, increasing the content of a ferromagnetic material and biochemical functionalization involving the attachment of the key addresses. The ferromagnetic nanocontainers were synthesised in CVD and microwave plasma system. The research work has been financed from the budget of science as a research project No. PBS2/A5/31/2013.

Keywords: hyperthermia, carbon nanotubes, cancer colon cells, radio frequency field

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18940 The Influence of Polysaccharide Isolated from Morinda citrifolia Fruit to the Growth of Vero, He-La and T47D Cell Lines against Doxorubicin in vitro

Authors: Ediati Budi Cahyono, Triana Hertiani, Nauval Arrazy Asawimanda, Wahyu Puji Pratomo

Abstract:

Background: Doxorubicin is widely used as a chemotherapeutic drug despite having many side effects. It may cause macrophage dysfunction and decreasing proliferation of lymphocyte. Noni (Morinda citrifolia) fruit which has rich of polysaccharide content has potential as antitumor and immunostimulant effect. The isolation of polysaccharide from Noni fruit has been optimized according to four different methods based on macrophage and lymphocyte activities. We found the highest polysaccharide content from one of the four methods isolation. A method of polysaccharide isolation which has the highest immunostimulant effect was used for further observation as co-chemotherapy. The aim of the study: was to evaluate the isolated polysaccharide from the method of choice as co-chemotherapy of doxorubicin for the growth of Vero, He-La, and T47D cell lines in vitro. The method: in vitro growth assay of Vero, He-La, and T47D cell lines was done using MTT-reduction method, and apoptosis test was done by double staining method to evaluate the induction apoptotic effect of the combination. Every group was treated with doxorubicin and isolated polysaccharide from method of choice with 4 variances of concentrations (25 µg/ml, 50 µg/ml, 100 µg/ml and 200 µg/ml) a long with negative control (doxorubicin only) and normal control (without doxorubicin or polysaccharide administration). Results: The combination of polysaccharide fraction in the concentration of 100μg/ml with 2μmol of doxorubicin against He-La and T47D cell lines influenced the highest cytotoxic effect by suppressing cell viability comparing with doxorubicin only. The combination of polysaccharide fraction in the concentration of 100μg/ml with 2μmol of doxorubicin-induced apoptotic effect the He-La cell line comparing with doxorubicin only. The result of the study: it can be concluded that the combination of polysaccharide fraction and doxorubicin effect more selective toward He-La and T47D cell lines than to Vero cell line. It can be suggested isolated polysaccharide from the method of choice has co-chemotherapy activity against doxorubicin.

Keywords: polysaccharide, noni fruit, doxorubicin, cancer cell lines, vero cell line

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18939 Numerical Simulation of Rayleigh Benard Convection and Radiation Heat Transfer in Two-Dimensional Enclosure

Authors: Raoudha Chaabane, Faouzi Askri, Sassi Ben Nasrallah

Abstract:

A new numerical algorithm is developed to solve coupled convection-radiation heat transfer in a two dimensional enclosure. Radiative heat transfer in participating medium has been carried out using the control volume finite element method (CVFEM). The radiative transfer equations (RTE) are formulated for absorbing, emitting and scattering medium. The density, velocity and temperature fields are calculated using the two double population lattice Boltzmann equation (LBE). In order to test the efficiency of the developed method the Rayleigh Benard convection with and without radiative heat transfer is analyzed. The obtained results are validated against available works in literature and the proposed method is found to be efficient, accurate and numerically stable.

Keywords: participating media, LBM, CVFEM- radiation coupled with convection

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18938 A New Authenticable Steganographic Method via the Use of Numeric Data on Public Websites

Authors: Che-Wei Lee, Bay-Erl Lai

Abstract:

A new steganographic method via the use of numeric data on public websites with self-authentication capability is proposed. The proposed technique transforms a secret message into partial shares by Shamir’s (k, n)-threshold secret sharing scheme with n = k + 1. The generated k+1 partial shares then are embedded into the selected numeric items in a website as if they are part of the website’s numeric content. Afterward, a receiver links to the website and extracts every k shares among the k+1 ones from the stego-numeric-content to compute k+1 copies of the secret, and the phenomenon of value consistency of the computed k+1 copies is taken as an evidence to determine whether the extracted message is authentic or not, attaining the goal of self-authentication of the extracted secret message. Experimental results and discussions are provided to show the feasibility and effectiveness of the proposed method.

Keywords: steganography, data hiding, secret authentication, secret sharing

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18937 Research of the Activation Energy of Conductivity in P-I-N SiC Structures Fabricated by Doping with Aluminum Using the Low-Temperature Diffusion Method

Authors: Ilkham Gafurovich Atabaev, Khimmatali Nomozovich Juraev

Abstract:

The activation energy of conductivity in p-i-n SiC structures fabricated by doping with Aluminum using the new low-temperature diffusion method is investigated. In this method, diffusion is stimulated by the flux of carbon and silicon vacancies created by surface oxidation. The activation energy of conductivity in the p - layer is 0.25 eV and it is close to the ionization energy of Aluminum in 4H-SiC from 0.21 to 0.27 eV for the hexagonal and cubic positions of aluminum in the silicon sublattice for weakly doped crystals. The conductivity of the i-layer (measured in the reverse biased diode) shows 2 activation energies: 0.02 eV and 0.62 eV. Apparently, the 0.62 eV level is a deep trap level and it is a complex of Aluminum with a vacancy. According to the published data, an analogous level system (with activation energies of 0.05, 0.07, 0.09 and 0.67 eV) was observed in the ion Aluminum doped 4H-SiC samples.

Keywords: activation energy, aluminum, low temperature diffusion, SiC

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18936 'Sex, Work and Sex-Work': The Clandestine Tale of a Tabooed Industry in Bangladesh

Authors: Parvez Sattar

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There are around 150,000 female sex workers in Bangladesh, and the country hosts one of the largest brothels in the world. There are 20 brothel-villages in the country, of which 14 are recognized to be ‘official’, and at least 11 are currently operational. Although the national Constitution adopts a preventive policy against prostitution, law does not, as such, prohibit commercial sex work by an adult woman working in a brothel having made an affidavit in this regard. But, at the same time, the law renders at least some forms of floating and hotel based sex work illegal, while sex between males has been termed as sodomy and made culpable offence even on its own. All forms of sex works by MSM and Hijra are thus branded as criminal acts. Observations and findings drawn in this article are based on both primary and secondary sources collecting data from a series of field-based empirical studies conducted by the author through questionnaire survey, FGDs, key informant consultations and other PRA/PLA tools. General and specific conclusions have been based on analysis guided by international standards of human and labour rights approaches. It has been noted that neither the community attitudes nor the cultural mind-sets, or the State's institutional set up is supportive of the causes of sex workers engaged in the most exploitative forms of labour. Lack of respect for fundamental rights continues to diminish any chances of sex workers' reintegration to the mainstream of the society, perpetuates poverty, and increases their vulnerability to HIV/AIDS. To aggravate the scenario, the endemic practice of a complex debt-bondage masked by the so-called 'entry-cost' and ‘legal license’ to the industry is considered to be a somewhat accepted 'open secret' and that the police and administration keep their eyes off from such practices treating these as 'their internal affairs'. Often these practices are used by the Sardarni/Khala (landlady) and other 'managing' actors as the tool for further exploitation of the sex workers as well as a 'control strategy'. The paper concludes with the observation that the tabooed truths of commercial sex and sex workers are inherently embedded in the very factors that compel them into this endemically ostracised profession itself. While denial of both recognition and enjoyment of the fundamental human rights of sex workers is widespread, it is the same cycle of social vulnerability and economic exclusion that often confines these people within a continuous process of servitude and modern day slavery.

Keywords: commercial sex work and human rights, Labor protection in sex industry, Prostitution Law in Bangladesh, Sex work as modern day slavery

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18935 Drinking Water Quality Assessment Using Fuzzy Inference System Method: A Case Study of Rome, Italy

Authors: Yas Barzegar, Atrin Barzegar

Abstract:

Drinking water quality assessment is a major issue today; technology and practices are continuously improving; Artificial Intelligence (AI) methods prove their efficiency in this domain. The current research seeks a hierarchical fuzzy model for predicting drinking water quality in Rome (Italy). The Mamdani fuzzy inference system (FIS) is applied with different defuzzification methods. The Proposed Model includes three fuzzy intermediate models and one fuzzy final model. Each fuzzy model consists of three input parameters and 27 fuzzy rules. The model is developed for water quality assessment with a dataset considering nine parameters (Alkalinity, Hardness, pH, Ca, Mg, Fluoride, Sulphate, Nitrates, and Iron). Fuzzy-logic-based methods have been demonstrated to be appropriate to address uncertainty and subjectivity in drinking water quality assessment; it is an effective method for managing complicated, uncertain water systems and predicting drinking water quality. The FIS method can provide an effective solution to complex systems; this method can be modified easily to improve performance.

Keywords: water quality, fuzzy logic, smart cities, water attribute, fuzzy inference system, membership function

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18934 Health Trajectory Clustering Using Deep Belief Networks

Authors: Farshid Hajati, Federico Girosi, Shima Ghassempour

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We present a Deep Belief Network (DBN) method for clustering health trajectories. Deep Belief Network (DBN) is a deep architecture that consists of a stack of Restricted Boltzmann Machines (RBM). In a deep architecture, each layer learns more complex features than the past layers. The proposed method depends on DBN in clustering without using back propagation learning algorithm. The proposed DBN has a better a performance compared to the deep neural network due the initialization of the connecting weights. We use Contrastive Divergence (CD) method for training the RBMs which increases the performance of the network. The performance of the proposed method is evaluated extensively on the Health and Retirement Study (HRS) database. The University of Michigan Health and Retirement Study (HRS) is a nationally representative longitudinal study that has surveyed more than 27,000 elderly and near-elderly Americans since its inception in 1992. Participants are interviewed every two years and they collect data on physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The dataset is publicly available and we use the RAND HRS version L, which is easy to use and cleaned up version of the data. The size of sample data set is 268 and the length of the trajectories is equal to 10. The trajectories do not stop when the patient dies and represent 10 different interviews of live patients. Compared to the state-of-the-art benchmarks, the experimental results show the effectiveness and superiority of the proposed method in clustering health trajectories.

Keywords: health trajectory, clustering, deep learning, DBN

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18933 Nonlinear Free Surface Flow Simulations Using Smoothed Particle Hydrodynamics

Authors: Abdelraheem M. Aly, Minh Tuan Nguyen, Sang-Wook Lee

Abstract:

The incompressible smoothed particle hydrodynamics (ISPH) is used to simulate impact free surface flows. In the ISPH, pressure is evaluated by solving pressure Poisson equation using a semi-implicit algorithm based on the projection method. The current ISPH method is applied to simulate dam break flow over an inclined plane with different inclination angles. The effects of inclination angle in the velocity of wave front and pressure distribution is discussed. The impact of circular cylinder over water in tank has also been simulated using ISPH method. The computed pressures on the solid boundaries is studied and compared with the experimental results.

Keywords: incompressible smoothed particle hydrodynamics, free surface flow, inclined plane, water entry impact

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18932 Application of Liquid Chromatographic Method for the in vitro Determination of Gastric and Intestinal Stability of Pure Andrographolide in the Extract of Andrographis paniculata

Authors: Vijay R. Patil, Sathiyanarayanan Lohidasan, K. R. Mahadik

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Gastrointestinal stability of andrographolide was evaluated in vitro in simulated gastric (SGF) and intestinal (SIF) fluids using a validated HPLC-PDA method. The method was validated using a 5μm ThermoHypersil GOLD C18column (250 mm × 4.0 mm) and mobile phase consisting of water: acetonitrile; 70: 30 (v/v) delivered isocratically at a flow rate of 1 mL/min with UV detection at 228 nm. Andrographolide in pure form and extract Andrographis paniculata was incubated at 37°C in an incubator shaker in USP simulated gastric and intestinal fluids with and without enzymes. Systematic protocol as per FDA Guidance System was followed for stability study and samples were assayed at 0, 15, 30 and 60 min intervals for gastric and at 0, 15, 30, 60 min, 1, 2 and 3 h for intestinal stability study. Also, the stability study was performed up to 24 h to see the degradation pattern in SGF and SIF (with enzyme and without enzyme). The developed method was found to be accurate, precise and robust. Andrographolide was found to be stable in SGF (pH ∼ 1.2) for 1h and SIF (pH 6.8) up to 3 h. The relative difference (RD) of amount of drug added and found at all time points was found to be < 3%. The present study suggests that drug loss in the gastrointestinal tract takes place may be by membrane permeation rather than a degradation process.

Keywords: andrographolide, Andrographis paniculata, in vitro, stability, gastric, Intestinal HPLC-PDA

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18931 Enhancing Fault Detection in Rotating Machinery Using Wiener-CNN Method

Authors: Mohamad R. Moshtagh, Ahmad Bagheri

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Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

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18930 A Nonstandard Finite Difference Method for Weather Derivatives Pricing Model

Authors: Clarinda Vitorino Nhangumbe, Fredericks Ebrahim, Betuel Canhanga

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The price of an option weather derivatives can be approximated as a solution of the two-dimensional convection-diffusion dominant partial differential equation derived from the Ornstein-Uhlenbeck process, where one variable represents the weather dynamics and the other variable represent the underlying weather index. With appropriate financial boundary conditions, the solution of the pricing equation is approximated using a nonstandard finite difference method. It is shown that the proposed numerical scheme preserves positivity as well as stability and consistency. In order to illustrate the accuracy of the method, the numerical results are compared with other methods. The model is tested for real weather data.

Keywords: nonstandard finite differences, Ornstein-Uhlenbeck process, partial differential equations approach, weather derivatives

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18929 Selecting The Contractor using Multi Criteria Decision Making in National Gas Company of Lorestan Province of Iran

Authors: Fatemeh Jaferi, Moslem Parsa, Heshmatolah Shams Khorramabadi

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In this modern fluctuating world, organizations need to outsource some parts of their activities (project) to providers in order to show a quick response to their changing requirements. In fact, a number of companies and institutes have contractors do their projects and have some specific criteria in contractor selection. Therefore, a set of scientific tools is needed to select the best contractors to execute the project according to appropriate criteria. Multi-criteria decision making (MCDM) has been employed in the present study as a powerful tool in ranking and selecting the appropriate contractor. In this study, devolving second-source (civil) project to contractors in the National Gas Company of Lorestan Province (Iran) has been found and therefore, 5 civil companies have been evaluated. Evaluation criteria include executive experience, qualification of technical staff, good experience and company's rate, technical interview, affordability, equipment and machinery. Criteria's weights are found through experts' opinions along with AHP and contractors ranked through TOPSIS and AHP. The order of ranking contractors based on MCDM methods differs by changing the formula in the study. In the next phase, the number of criteria and their weights has been sensitivity analysed through using AHP. Adding each criterion changed contractors' ranking. Similarly, changing weights resulted in a change in ranking. Adopting the stated strategy resulted in the facts that not only is an appropriate scientific method available to select the most qualified contractors to execute gas project, but also a great attention is paid to picking needed criteria for selecting contractors. Consequently, executing such project is undertaken by most qualified contractors resulted in optimum use of limited resource, accelerating the implementation of project, increasing quality and finally boosting organizational efficiency.

Keywords: multi-criteria decision making, project, management, contractor selection, gas company

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18928 Fallacies of Argumentation in Modern American Political Discourse

Authors: Zarine Avetisyan

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The process of speech production and transmission naturally implies the occurrence of certain defective assumptions and erroneous formulations which may be both spontaneous, caused by haste, carelessness, etc., or deliberate. Whether deliberate or not, fallacies always act by way of “faux pas”. In the latter case, we deal with fake or deceptive arguments which are the focus of the given paper. The paper departs from the assumption that fallacies are arguments that prove nothing. Additionally and more importantly, political discourse becomes the main domain for scholarly “cultivation” while pinning down fallacies. The fallacy of telling the truth but deliberately omitting important key details in order to falsify the larger picture called “the half truth” captures special attention in the given paper.

Keywords: break in the information chain, fallacy, half truth, political discourse

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18927 An Image Stitching Approach for Scoliosis Analysis

Authors: Siti Salbiah Samsudin, Hamzah Arof, Ainuddin Wahid Abdul Wahab, Mohd Yamani Idna Idris

Abstract:

Standard X-ray spine images produced by conventional screen-film technique have a limited field of view. This limitation may obstruct a complete inspection of the spine unless images of different parts of the spine are placed next to each other contiguously to form a complete structure. Another solution to producing a whole spine image is by assembling the digitized x-ray images of its parts automatically using image stitching. This paper presents a new Medical Image Stitching (MIS) method that utilizes Minimum Average Correlation Energy (MACE) filters to identify and merge pairs of x-ray medical images. The effectiveness of the proposed method is demonstrated in two sets of experiments involving two databases which contain a total of 40 pairs of overlapping and non-overlapping spine images. The experimental results are compared to those produced by the Normalized Cross Correlation (NCC) and Phase Only Correlation (POC) methods for comparison. It is found that the proposed method outperforms those of the NCC and POC methods in identifying both the overlapping and non-overlapping medical images. The efficacy of the proposed method is further vindicated by its average execution time which is about two to five times shorter than those of the POC and NCC methods.

Keywords: image stitching, MACE filter, panorama image, scoliosis

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18926 Wearable Music: Generation of Costumes from Music and Generative Art and Wearing Them by 3-Way Projectors

Authors: Noriki Amano

Abstract:

The final goal of this study is to create another way in which people enjoy music through the performance of 'Wearable Music'. Concretely speaking, we generate colorful costumes in real- time from music and to realize their dressing by projecting them to a person. For this purpose, we propose three methods in this study. First, a method of giving color to music in a three-dimensionally way. Second, a method of generating images of costumes from music. Third, a method of wearing the images of music. In particular, this study stands out from other related work in that we generate images of unique costumes from music and realize to wear them. In this study, we use the technique of generative arts to generate images of unique costumes and project the images to the fog generated around a person from 3-way using projectors. From this study, we can get how to enjoy music as 'wearable'. Furthermore, we are also able to have the prospect of unconventional entertainment based on the fusion between music and costumes.

Keywords: entertainment computing, costumes, music, generative programming

Procedia PDF Downloads 159
18925 Taguchi Method for Analyzing a Flexible Integrated Logistics Network

Authors: E. Behmanesh, J. Pannek

Abstract:

Logistics network design is known as one of the strategic decision problems. As these kinds of problems belong to the category of NP-hard problems, traditional ways are failed to find an optimal solution in short time. In this study, we attempt to involve reverse flow through an integrated design of forward/reverse supply chain network that formulated into a mixed integer linear programming. This Integrated, multi-stages model is enriched by three different delivery path which makes the problem more complex. To tackle with such an NP-hard problem a revised random path direct encoding method based memetic algorithm is considered as the solution methodology. Each algorithm has some parameters that need to be investigate to reveal the best performance. In this regard, Taguchi method is adapted to identify the optimum operating condition of the proposed memetic algorithm to improve the results. In this study, four factors namely, population size, crossover rate, local search iteration and a number of iteration are considered. Analyzing the parameters and improvement in results are the outlook of this research.

Keywords: integrated logistics network, flexible path, memetic algorithm, Taguchi method

Procedia PDF Downloads 175
18924 Bright, Dark N-Soliton Solution of Fokas-Lenells Equation Using Hirota Bilinearization Method

Authors: Sagardeep Talukdar, Riki Dutta, Gautam Kumar Saharia, Sudipta Nandy

Abstract:

In non-linear optics, the Fokas-Lenells equation (FLE) is a well-known integrable equation that describes how ultrashort pulses move across the optical fiber. It admits localized wave solutions, just like any other integrable equation. We apply the Hirota bilinearization method to obtain the soliton solution of FLE. The proposed bilinearization makes use of an auxiliary function. We apply the method to FLE with a vanishing boundary condition, that is, to obtain a bright soliton solution. We have obtained bright 1-soliton and 2-soliton solutions and propose a scheme for obtaining an N-soliton solution. We have used an additional parameter that is responsible for the shift in the position of the soliton. Further analysis of the 2-soliton solution is done by asymptotic analysis. In the non-vanishing boundary condition, we obtain the dark 1-soliton solution. We discover that the suggested bilinearization approach, which makes use of the auxiliary function, greatly simplifies the process while still producing the desired outcome. We think that the current analysis will be helpful in understanding how FLE is used in nonlinear optics and other areas of physics.

Keywords: asymptotic analysis, fokas-lenells equation, hirota bilinearization method, soliton

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18923 Research and Development of Methodology, Tools, Techniques and Methods to Analyze and Design Interface, Media, Pedagogy for Educational Topics to be Delivered via Mobile Technology

Authors: Shimaa Nagro, Russell Campion

Abstract:

Mobile devices are becoming ever more widely available, with growing functionality, and they are increasingly used as enabling technology to give students access to educational material anytime and anywhere. However, the design of educational material's user interfaces for mobile devices is beset by many unresolved research problems such as those arising from constraints associated with mobile devices or from issues linked to effective learning. The proposed research aims to produce: (i) a method framework for the design and evaluation of educational material’s interfaces to be delivered on mobile devices, in multimedia form based on Human Computer Interaction strategies; and (ii) a software tool implemented as a fast-track alternative to use the method framework in full. The investigation will combine qualitative and quantitative methods, including interviews and questionnaires for data collection and three case studies for validating the method framework. The method framework is a framework to enable an educational designer to effectively and efficiently create educational multimedia interfaces to be used on mobile devices by following a particular methodology that contains practical and usable tools and techniques. It is a method framework that accepts any educational material in its final lesson plan and deals with this plan as a static element, it will not suggest any changes in any information given in the lesson plan but it will help the instructor to design his final lesson plan in a multimedia format to be presented in mobile devices.

Keywords: mobile learning, M-Learn, HCI, educational multimedia, interface design

Procedia PDF Downloads 357
18922 Mentha piperita Formulations in Natural Deep Eutectic Solvents: Phenolic Profile and Biological Activity

Authors: Tatjana Jurić, Bojana Blagojević, Denis Uka, Ružica Ždero Pavlović, Boris M. Popović

Abstract:

Natural deep eutectic solvents (NADES) represent a class of modern systems that have been developed as a green alternative to toxic organic solvents, which are commonly used as extraction media. It has been considered that hydrogen bonding is the main interaction leading to the formation of NADES. The aim of this study was phytochemical characterization and determination of the antioxidant and antibacterial activity of Mentha piperita leaf extracts obtained by six choline chloride-based NADES. NADES were prepared by mixing choline chloride with different hydrogen bond donors in 1:1 molar ratio following the addition of 30% (w/w) water. The mixtures were then heated (60 °C) and stirred (650 rpm) until the clear homogenous liquids were obtained. The Mentha piperita extracts were prepared by mixing 75 mg of peppermint leaves with 1 mL of NADES following by the heating and stirring (60 °C, 650 rpm) within 30 min. The content of six phenolics in extracts was determined using HPLC-PDA. The dominant compounds presented in peppermint leaves - rosmarinic acid and luteolin 7-O-glucoside, were extracted by NADES at a similar level as 70% ethanol. The microdilution method was applied to test the antibacterial activity of extracts. Compared with 70% ethanol, all NADES systems showed higher antibacterial activity towards Pseudomonas aeruginosa (Gram -), Staphylococcus aureus (Gram +), Escherichia coli (Gram -), and Salmonella enterica (Gram -), especially NADES containing organic acids. The majority of NADES extracts showed a better ability to neutralize DPPH radical than conventional solvent and similar ability to reduce Fe3+ to Fe2+ ions in FRAP assay. The obtained results introduce NADES systems as the novel, sustainable, and low-cost solvents with a variety of applications.

Keywords: antibacterial activity, antioxidant activity, green extraction, natural deep eutectic solvents, polyphenols

Procedia PDF Downloads 169
18921 Risk Management in Industrial Supervision Projects

Authors: Érick Aragão Ribeiro, George André Pereira Thé, José Marques Soares

Abstract:

Several problems in industrial supervision software development projects may lead to the delay or cancellation of projects. These problems can be avoided or contained by using identification methods, analysis and control of risks. These procedures can give an overview of the possible problems that can happen in the projects and what are the immediate solutions. Therefore, we propose a risk management method applied to the teaching and development of industrial supervision software. The method is developed through a literature review and previous projects can be divided into phases of management and have basic features that are validated with experimental research carried out by mechatronics engineering students and professionals. The management is conducted through the stages of identification, analysis, planning, monitoring, control and communication of risks. Programmers use a method of prioritizing risks considering the gravity and the possibility of occurrence of the risk. The outputs of the method indicate which risks occurred or are about to happen. The first results indicate which risks occur at different stages of the project and what risks have a high probability of occurring. The results show the efficiency of the proposed method compared to other methods, showing the improvement of software quality and leading developers in their decisions. This new way of developing supervision software helps students identify design problems, evaluate software developed and propose effective solutions. We conclude that the risk management optimizes the development of the industrial process control software and provides higher quality to the product.

Keywords: supervision software, risk management, industrial supervision, project management

Procedia PDF Downloads 334
18920 Satellite Imagery Classification Based on Deep Convolution Network

Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

Abstract:

Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization

Procedia PDF Downloads 282